project_data_summary
Camille Leclerc
14/02/2022
0. Hypothesis
0.1 Short rational
Temperature and enrichment are predicted to have dramatic impacts on food-webs
Stability is theoretically predicted to have an U-shape with temperature (Uszko et al. 2017), higher temperature leading to higher stability in “cold” food-webs, and to lower stability in “hot” food-webs
Futhermore, metabolic theory predicts that higher trophic level suffer most from high temperature. Metabolic costs increase exponentially with temperature and higher trophic levels have generally higher body mass and then higher basal metabolic cost
Enrichment (measured here by DBO), is predicted to decrease stability by increasing the amplitude of population fluctuations (Rosenzweig 1971)
Insterestingly, enrichment is predicted to dampens the effect of high temperature by increasing resources thereby decreasing starvation risk due to high temperature (Tabi, Petchey, and Pennekamp 2019)
Stream and lakes are really different ecosystems:
- Stream fishes are highly contrained by stream flow
- Lakes are highly vertically stratified but offer limited opportunity for dispersal
- Streams are horizontal stratified and offer opportunity for dispersal
Develop hypothesis:
- about differences between lakes and streams…
- about the different network metrics
0.2 Methods
- Network metrics: Connectance, Max trophic level, Mean trophic level, number of nodes
- Environment: Temperature and DBO (to detail)
0.3 Statistical ideas
- Simple linear model:
\(N_i = \alpha + \beta_0F + \beta_1T_i + \beta_2T_iF + \beta_3D_i + \beta_4D_iF + \beta_5D_iT_i \beta_6D_iT_iF+ \epsilon\)
- With:
- \(i\): site i
- \(N_i\): Network metric of site \(i\)
- \(D\): DBO
- \(T\): Temperature
- \(F\): freshwater ecosystem type, lake or stream (logical variable ?)
- \(\alpha\): intercept
- \(\beta\): slope
- \(\beta_2\), \(\beta_4\), \(\beta_5\): slope of simple interaction
- \(\beta_2\): link between network metrics and temperature change with ecosystem type ?
- \(\beta_4\): link between network metrics and DBO change with ecosystem type ?
- \(\beta_5\): link between network metrics and DBO change with temperature ? (hyp enrichment and temperature compensate each other)
- \(\beta_6\): slope of triple interaction; effect of temperature on the link between network metrics and DBO change with ecosystem type ?
- Structural Equation Model (one for each ecosystem type ?) (Gibert 2019):
We certainly need to assess the collinearity among network descriptors in the SEM, it may be high, but it was ok in (Danet et al. 2021).
1. Temporal and spatial coverage
Due to biological and environmental data availability, the temporal coverage is from 2007 to 2016.
91 sampled lakes and 274 sampled stream stations were considered.
2. Environmental variables
| variable | mean | sd | median | min | max | mean | sd | median | min | max |
|---|---|---|---|---|---|---|---|---|---|---|
| dbo (mg/L) | 1.5 | 0.9 | 1.3 | 0.5 | 5.5 | 1.6 | 0.6 | 1.5 | 0.6 | 4.9 |
| temperature (°C) | 13.9 | 1.9 | 13.6 | 9.6 | 18.5 | 11.3 | 1.9 | 11.3 | 1.8 | 17.8 |
3. Food web metrics
| metric | mean | sd | median | min | max | mean | sd | median | min | max |
|---|---|---|---|---|---|---|---|---|---|---|
| connectance | 0.1 | 0.0 | 0.1 | 0.1 | 0.2 | 0.2 | 0.0 | 0.2 | 0.1 | 0.2 |
| max trophic level | 4.0 | 0.2 | 4.0 | 3.1 | 4.5 | 3.8 | 0.2 | 3.8 | 2.9 | 4.4 |
| mean trophic level | 3.3 | 0.2 | 3.3 | 2.2 | 4.0 | 3.5 | 0.3 | 3.5 | 2.7 | 4.2 |
| number of nodes | 40.8 | 10.2 | 39.0 | 21.0 | 67.0 | 31.4 | 14.8 | 30.0 | 8.0 | 92.0 |
4. Environmental variables vs. Food web metrics
